Google Datastudio vs Looker

Overview

Looker

Stacks632

Followers656

Votes9

Google Datastudio

Stacks200

Followers170

Votes16

Google Datastudio vs Looker: What are the differences?

Developers describe Google Datastudio as "A reporting and data visualization tool". It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions. On the other hand, Looker is detailed as "Pioneering the next generation of BI, data discovery & data analytics". We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.

Google Datastudio and Looker can be primarily classified as "Business Intelligence" tools.

According to the StackShare community, Looker has a broader approval, being mentioned in 83 company stacks & 51 developers stacks; compared to Google Datastudio, which is listed in 8 company stacks and 4 developer stacks.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on Looker, Google Datastudio

Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k

Comments

Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k

Comments

Detailed Comparison

Looker	Google Datastudio
We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.	It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.
Zero-lag access to data;No limits;Personalized setup and support;No uploading, warehousing, or indexing;Deploy anywhere;Works in any browser, anywhere;Personalized access points	Easily access a wide variety of data. Data Studio’s built-in and partner connectors makes it possible to connect to virtually any kind of data Turn your data into compelling stories of data visualization art. Quickly build interactive reports and dashboards with Data Studio’s web based reporting tools Share your reports and dashboards with individuals, teams, or the world. Collaborate in real time. Embed your report on any web page
Statistics
Stacks 632	Stacks 200
Followers 656	Followers 170
Votes 9	Votes 16
Pros & Cons
Pros 4 Real time in app customer chat support 4 GitHub integration 1 Reduces the barrier of entry to utilizing data Cons 3 Price	Pros 6 Free 4 Underrated 2 Easy to share 1 Shareable & editable dashboards 1 BigQuery Integration Cons 1 Works well with google (not aws or azure)
Integrations
No integrations available	MySQL Microsoft SQL Server Microsoft Excel

What are some alternatives to Looker, Google Datastudio?

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Power BI

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.